Health and Wellness Measurements

Health & Wellness Measurements group

Multimodal brain imaging

We are the first research group in the world that has enabled measurements of blood pressure and cardiorespiratory signals in magnetic neuroimaging environments, particularly simultaneously with Magnetoencephalography (MEG) (Myllylä et al. 2017a) and Magnetic Resonance Imaging (MRI) (Myllylä et al 2011)

On the left, MEG multimodal setup. On the right, averaged responses of breath holds for different signal modalities (Figs. a-e) in human body and the brain, recorded with MEG multimodal setup. Fig. (f) shows an averaged response for magnetic resonance encephalography (MREG) when using the same breath hold task, recorded in MRI multimodal setup (Myllylä et al. 2017a, Korhonen et al. 2014). http://www.nature.com/articles/s41598-017-00293-7/figures/7

One of our main focuses is on brain research and development of these related imaging techniques, also for wearable use. The study activities are conducted in close collaboration with Oulu Functional Neuroimaging group (OFNI), located also in University of Oulu. We combine existing and novel brain sensing techniques. Currently, optical, capacitive and microwave based imaging techniques are under development.

In particular, one of the special focuses is on brain clearance mechanism and the glymphatic system (Zienkiewicz et al. 2017). Using the combined techniques we can measure, such as, cerebral hemodynamics, blood volume and flow, water dynamics in the brain cortex and changes in dielectric properties of brain tissue (Myllylä et al. 2017b). These techniques can be utilized for detecting such as brain hematomas and edema, pain, stages of sleep. Furthermore, these techniques are extensively utilized in several brain research areas conducted together with collaborating partners in USA, Europe and Asian.

In addition to brain imaging, we employ and develop different wearable biomedical sensors to acquire data on human health and wellness in clinical and home environments. For instance, for muscle contraction measurement we use a combined surface electromyography (sEMG), NIRS and acceleration measurement technique (Kauppi et al. 2016). For accurate measurement of human body balance we utilize the latest MEMS sensing techniques (Sanz et al. 2016).

One of the current projects in human wellness measurements is the Bulstop project to prevent school violence by utilizing wearable sensor technology. So far, the school violence detection is based on movement, electrocardiography (ECG), speech and electroencephalography (EEG). We have conducted several school violence simulations in Finland, Indonesia, and China with promising results.

Based on the collected data, violence event was detected from ECG signal with accuracy around 95%. The ECG signal is analyzed with the Bivariate Empirical Mode Decomposition (BEMD). Based on the movement, we can distinguish normal daily activities from movement related to violence with accuracy up to 90% (Ferdinando et al. 2017).

Wellness measurements include also monitoring the environment we are living. Using wearable and/or small sensors we can measure different environmental parameters that may affect human wellness e.g. noise, lightning or water quality (Hakala & Myllylä 2016). Further, we can study how these affect human health.